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» Geodesic Deformable Models for Medical Image Analysis
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MICCAI
2009
Springer
16 years 4 months ago
Nonparametric Mean Shift Functional Detection in the Functional Space for Task and Resting-state fMRI
In functional Magnetic Resonance Imaging (fMRI) data analysis, normalization of time series is an important and sometimes necessary preprocessing step in many widely used methods. ...
Jian Cheng, Feng Shi, Kun Wang, Ming Song, Jiefeng...
MICCAI
2009
Springer
16 years 5 months ago
Multimodal Prior Appearance Models Based on Regional Clustering of Intensity Profiles
Model-based image segmentation requires prior information about the appearance of a structure in the image. Instead of relying on Principal Component Analysis such as in Statistica...
François Chung, Hervé Delingette
ICIP
2006
IEEE
16 years 5 months ago
A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
IPMI
2011
Springer
14 years 7 months ago
Surface-Region Context in Optimal Multi-object Graph-Based Segmentation: Robust Delineation of Pulmonary Tumors
Abstract. Multi-object segmentation with mutual interaction is a challenging task in medical image analysis. We report a novel solution to a segmentation problem, in which target o...
Qi Song, Mingqing Chen, Junjie Bai, Milan Sonka, X...
ISBI
2006
IEEE
16 years 4 months ago
Mixture principal component analysis for distribution volume parametric imaging in brain PET studies
In this paper, we present a mixture Principal Component Analysis (mPCA)-based approach for voxel level quantification of dynamic positron emission tomography (PET) data in brain s...
Peng Qiu, Z. Jane Wang, K. J. Ray Liu